mindnet/app/core/chunking/chunking_strategies.py

142 lines
5.6 KiB
Python

"""
FILE: app/core/chunking/chunking_strategies.py
DESCRIPTION: Korrigierte Splitting-Strategien für Mindnet v3.3.3.
- Fix: Erhalt von Überschriften im Chunk-Text.
- Fix: Atomares Buffering (Blöcke fallen als Ganzes in den nächsten Chunk).
- Fix: Korrekte Zuordnung von Sektions-Metadaten.
"""
from typing import List, Dict, Any, Optional
from .chunking_models import RawBlock, Chunk
from .chunking_utils import estimate_tokens
from .chunking_parser import split_sentences
def _create_context_win(doc_title: str, sec_title: Optional[str], text: str) -> str:
"""Baut den Breadcrumb-Kontext für das Embedding-Fenster."""
parts = []
if doc_title: parts.append(doc_title)
if sec_title and sec_title != doc_title: parts.append(sec_title)
prefix = " > ".join(parts)
return f"{prefix}\n{text}".strip() if prefix else text
def strategy_by_heading(blocks: List[RawBlock], config: Dict[str, Any], note_id: str, doc_title: str = "") -> List[Chunk]:
"""
Splittet Text basierend auf Markdown-Überschriften mit atomarem Block-Erhalt.
"""
strict = config.get("strict_heading_split", False)
target = config.get("target", 400)
max_tokens = config.get("max", 600)
split_level = config.get("split_level", 2)
overlap = sum(config.get("overlap", (50, 80))) // 2
chunks: List[Chunk] = []
buf: List[RawBlock] = []
cur_tokens = 0
def _add_to_chunks(txt, title, path):
idx = len(chunks)
win = _create_context_win(doc_title, title, txt)
chunks.append(Chunk(
id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx,
text=txt, window=win, token_count=estimate_tokens(txt),
section_title=title, section_path=path,
neighbors_prev=None, neighbors_next=None
))
def _flush():
nonlocal buf, cur_tokens
if not buf: return
# Metadaten stammen immer vom ersten Block im Puffer (meist die Überschrift)
main_title = buf[0].section_title
main_path = buf[0].section_path
full_text = "\n\n".join([b.text for b in buf])
# Falls der gesamte Puffer in einen Chunk passt
if estimate_tokens(full_text) <= max_tokens:
_add_to_chunks(full_text, main_title, main_path)
else:
# Nur wenn ein einzelner Abschnitt größer als 'max' ist, wird intern gesplittet
sents = split_sentences(full_text)
cur_sents = []; sub_len = 0
for s in sents:
slen = estimate_tokens(s)
if sub_len + slen > target and cur_sents:
_add_to_chunks(" ".join(cur_sents), main_title, main_path)
ov_s = []; ov_l = 0
for os in reversed(cur_sents):
if ov_l + estimate_tokens(os) < overlap:
ov_s.insert(0, os); ov_l += estimate_tokens(os)
else: break
cur_sents = list(ov_s); cur_sents.append(s); sub_len = ov_l + slen
else: cur_sents.append(s); sub_len += slen
if cur_sents: _add_to_chunks(" ".join(cur_sents), main_title, main_path)
buf = []; cur_tokens = 0
for b in blocks:
b_tokens = estimate_tokens(b.text)
# Prüfung auf Split-Trigger (Überschriften)
is_split_trigger = False
if b.kind == "heading":
if b.level < split_level:
is_split_trigger = True
elif b.level == split_level:
if strict or cur_tokens >= target:
is_split_trigger = True
if is_split_trigger:
_flush() # Vorherigen Puffer leeren
buf.append(b) # Neue Überschrift in den neuen Puffer aufnehmen
cur_tokens = b_tokens
else:
# Atomarer Check: Wenn der neue Block den aktuellen Chunk sprengen würde
if cur_tokens + b_tokens > max_tokens and buf:
_flush() # Puffer leeren, Block 'b' wird Teil des nächsten Chunks
buf.append(b)
cur_tokens += b_tokens
_flush() # Letzten Puffer leeren
return chunks
def strategy_sliding_window(blocks: List[RawBlock],
config: Dict[str, Any],
note_id: str,
context_prefix: str = "") -> List[Chunk]:
"""
Standard Sliding Window mit Korrektur für Heading-Retention.
"""
target = config.get("target", 400)
max_tokens = config.get("max", 600)
overlap_val = config.get("overlap", (50, 80))
overlap = sum(overlap_val) // 2 if isinstance(overlap_val, tuple) else overlap_val
chunks: List[Chunk] = []
buf: List[RawBlock] = []
def _flush_window():
nonlocal buf
if not buf: return
txt = "\n\n".join([b.text for b in buf])
idx = len(chunks)
win = f"{context_prefix}\n{txt}".strip() if context_prefix else txt
chunks.append(Chunk(
id=f"{note_id}#c{idx:02d}", note_id=note_id, index=idx,
text=txt, window=win, token_count=estimate_tokens(txt),
section_title=buf[0].section_title, section_path=buf[0].section_path,
neighbors_prev=None, neighbors_next=None
))
buf = []
for b in blocks:
# Auch hier: Überschriften mitnehmen
b_tokens = estimate_tokens(b.text)
current_buf_tokens = estimate_tokens("\n\n".join([x.text for x in buf])) if buf else 0
if current_buf_tokens + b_tokens >= target and buf:
_flush_window()
buf.append(b)
_flush_window()
return chunks